Agentic AI for Simulations Workflows

Workflows play critical role in science and engineering. Development of robust simulations workflows is challenging due to the need to link multiple models, often coming from different sources and in absence of data exchange standards. We propose an agentic AI framework for building simulation workflows using large language models (LLMs) with domain knowledge driving algorithms discovery and code generation. We believe that such approach can achieve significant reduction in workflows development time and more generally be used in automated and autonomous scientific discovery.